Software Developers Journey Podcast

#160 Amir Sadoughi built his career on curiosity


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Tim Bourguignon 0:07
Hello, and welcome to developer's journey, the podcast bringing you the making of stories of successful software developers to help you on your upcoming journey. My name is Tim O'Neill. And on this episode of 160, I received Amir suddenly, I'm here is currently the head of engineering at Pine Cone. He is a technical leader with over a decade of experience leading efforts in distributed systems. His career spans multiple industries, including machine learning, cloud computing, and high frequency trading. Amir, welcome to the afternoon.

Amir Saoughi 0:39
Thanks, Sam. Thanks for having me.

Tim Bourguignon 0:40
But before we come to your story, I want to thank those listeners who support the show every month, and help me pay for the editing, hosting and publishing deals. Paula Liu, and B, thank you so much for your generous donations. If you'd like to join this fine crew, go to our website at Dev journey dot info, and click on the orange support me on Patreon button. Every amount helps. Thank you. And now back to today's guest. I'm here. As you know, the show exists to help the listeners understand what your story look like and imagine how to shape their own future. So as always, let's go back to your beginning showing. Where would you place the start of your depth history?

Amir Saoughi 1:26
Sure, yeah, I guess I would start my journey at the very beginning. And I would split it across the three decades I've been here on Earth. So the first decade I would say my parents are both like educators. And so that was kind of the environment I grew up in. So I started with my first PC was if I remember correctly, specific bill, I'm gonna say 286 dx two is a very early until Windows 3.1 machine. And yeah, I got exposed to computers that early age, my dad briefly ran a internet cafe at a beach for a couple of years in the mid 90s. And yeah, I got exposed to all the different software packages people could install. I guess Netscape Navigator and Diablo are all the rage. Those days? Yeah, I think that's where I was start.

Tim Bourguignon 2:20
Did you right away feeling interested with this and put your hands in there? Or were you more more like a user? How do you relate to to this computer field in this first decade?

Amir Saoughi 2:30
Yeah, that first second. I obviously did not start programming. But yeah, it's more of a user. Like there was educational games, video games, just Yeah. The birth of the Internet, World Wide Web and just learning how to use computer. Yeah, just getting started.

Tim Bourguignon 2:46
Do you have some somebody knowledgeable with you to to guide you through this? Or how do you acquire knowledge?

Amir Saoughi 2:51
And the first? Yeah, like I just yeah, like any kid with an iPad these days, like you just kind of start using it and playing around with it and just, you know, self reinforcement learning feedback loops of trying different things and sometimes breaking them and sometimes putting it back together. But

Tim Bourguignon 3:07
so so having to format your hard drive a couple times a year, because nothing's working anymore. I have no idea how my parents have bared with me. I destroyed the computer trying everything trying all the options.

Amir Saoughi 3:20
Yeah, I guess that part of my distraction. I guess that didn't start until I guess the second decade. So that's learning about like Red Hat Linux seven or something like this and trying to dual boot the family PC to use Linux and Windows and probably destroyed a couple of the the hard drives in the process.

Tim Bourguignon 3:37
To get into Linux,

Amir Saoughi 3:38
it's hard to remember I remember must have been Yeah, family friend had shown that he had run Gentoo Linux on his machine. And I was like, oh, okay, you can compile this from source. But is there a faster way to get up and running? And he introduced me to Red Hat at that time? I

Tim Bourguignon 3:52
believe, okay. You fell directly to it? Why?

Amir Saoughi 3:55
Maybe this was after I started had started learning programming. Yeah, I guess I would say in the second decade. My parents again, yeah. As educators kind of reinforced learning. In in me. So like, in seventh grade, eighth grade, I was actually able to, like attend community college and get like the a plus certification, which is like how to become like a computer technician and build your own computer and stuff like this. And learning programming like I started with, like, quick, basic. I don't know if that's still available on MS DOS on Windows. But yeah, that's kind of where I started programming. And then once you start programming, you're like, oh, okay, what are some things I can do with the machine and you want to get more into the internals? And I think Linux is just Yeah, people use it as the most common development platform out there today. And there's a long journey to get there. But yeah, certainly taken over the cloud computing world. Okay, yeah,

Tim Bourguignon 4:47
that doesn't make sense. If you started with programming and then moved over to to Linux. I kind of understood at first that you went to Linux and then you move to programming and that would be something I had never heard before. Nowadays with Ubuntu when very, very high level of distress, then you could be a user right away on the next, but it's still uncommon. And so back then that would have been really uncommon. Okay, what did you do with with those programming skills? Did you have some projects already? Did you do something useful for yourself? Do you start selling software? Why did you hone the skills

Amir Saoughi 5:20
dramatically across my career is just like following my own curiosity, getting my hands dirty, and wanting to learn more about building things and and how things work that started with programming led me to kind of interested in like security and kind of robotics at the time. So this is mostly like during high school, I guess, or primary school, depending on where you live. But my two main interests were security and robotics. And I think just purely, it was interesting, because back in the early 2000s, like sequel, Slammer was like a big worm computer worm that had come out that basically, like destroyed tons of machines in a very rapid amount of time. And it was like, wow, that's like network computers, like the effect of software on those network computers. And then exploiting on top of that was just like layers of just complexity that just fascinated me.

Tim Bourguignon 6:09
So did you start exploring this deeper and deeper and deeper, just for the sake of it?

Amir Saoughi 6:14
Yeah, I tended to be more interested in like learning assembly and C++ and the low level languages, and getting my hands dirty with learning how the security software exploits work and understanding like, the basics of like buffer overflows. And well, it's been a while since I've done security, but yeah, things like that, of that. That nature. I think we're just fascinating, because security kind of looks like magic. Sometimes we're like, oh, you can remotely run something on somebody else's computer. Right? It's fascinating.

Tim Bourguignon 6:44
It isn't, do you have an idea of what your your professional would be something like 10 years later?

Amir Saoughi 6:50
No, not really. I mean, I kind of like I said, Follow my curiosity. So other than security, I was also interested in robotics. In high school, I was fortunate enough to also be part of like a robotics club where we would build Legos into like, robots. To achieve this competition. They had some C programming language that could actually flash the actual RFC device. And you'd have like a four foot by eight foot board and less than 10 minutes to manipulate these balls with these Lego size like Lego cat sized robots. So yeah, I think just like manipulating bits in the physical world is also just fascinating with robots. Because, you know, there's always that dream of like, you have a robot that fetches up or mow your lawn for you. And I always have my head in the future. I feel like so yeah, that also was a draw for me.

Tim Bourguignon 7:37
Fortunately, robots fetching beers are still in the future will probably be for a long time. They will be doing a lot of other things before they can do that.

Amir Saoughi 7:48
Yes, yeah, I guess we yeah, we got Yeah, drizzly instead of that sounds good.

Tim Bourguignon 7:52
Absolutely. When you when came the the decision point to, to decide where you want to go? What you want to study? Did you want to do robotics? Did you decide on security? Did you want another route? How did it go?

Amir Saoughi 8:08
Yeah, once I went to college, I went to UC Berkeley for college, I kind of explored both, like, I took upper division courses in both security and was also part of a robotics lab. And at that time, at that time, you know, deep learning and machine learning weren't like, technically around. I mean, technically, they're out since the 80s. But like the the current mode that we're operating in, hadn't been around because of the advances in in big data and neural networks that we have now. But at that time, yeah, I did see my career, like I was interested in applying those kinds of things that I had learned from dealing with robotics to kind of software. And so that kind of led me to my first job where I was helping build machine learning infrastructure, and kind of financial infrastructure for proprietary trading in the high frequency trading world, because it kind of fascinated me that you have this kind of closed loop system where you could kind of test your software ideas and models in the market without having a customer and you can iterate quickly. Yeah, that's kind of what led me to my first job.

Tim Bourguignon 9:08
So it's really quickly you mean making micro transaction transactions and always getting some feedback and realizing if it's good if it's not in reinforcing this and going back and forth?

Amir Saoughi 9:16
Yeah, I guess by contrast to like enterprise software today, like we didn't have like a manager, right? It's just a bunch of engineers, building this infrastructure and models and just deploying it against the market. And then that was pretty much the entire business, right? You don't need all the facets of business that like enterprise software companies today. So I guess it's just doing the the hard engineering problems without the impact that you enjoy with enterprise software. So I realized that yeah, it was fun, really fun to like work on hard engineering problems, but the impact you're having in like, just doing high frequency trading is limited. I know some firms you know, try to do different things with open source and so on, but for the most part, not as much impact As you know, working at Rackspace, or AWS, where you have enterprise customers across multiple industry verticals, after that job, I transitioned to working at Rackspace, which was kind of on the opposite side of that world. So you have enterprise software, you might have financial customers, but the enterprise software world is kind of you have an impact that you're making with those customers, and you're making it in a broad way. And you're still doing the hard engineering problems in dealing with distributed systems. So I kind of got the best of both worlds in terms of hard problems and an impact. Once I transitioned to working in enterprise software,

Tim Bourguignon 10:36
how was it to go from from zero customer facing software to really customer facing software's? I guess the whole the whole metric on this on this high frequency was, are we making more money, and nobody's really using it, it's working on it on its own. And then on the other side, it's really customers giving you feedback and telling you Well, what you did is good. But from a UX standpoint, it's not what we expect from a user perspective, it's not what we want. I know, it's, it's not complicated anymore. It's complex. It's in the in the human space, I want to go from one to the other.

Amir Saoughi 11:05
I think it's, it's nice in a way, because it's easier to explain to your family what you're doing that in a way other than that, not that much easier, but it's a little bit easier to explain to them what you're doing. And I think the you know, from a customer perspective, I think it also makes it a bit easier, maybe not easier, but maybe more meritocratic to prioritize the roadmap, so to speak, because in that kind of Profit Loss world, you just have kind of managing director kind of overseeing the priorities, more or less. And here in kind of the enterprise software world, you have customers that you try to balance their, their needs. And what you see in the future roadmap, so it's, it's a nice transition.

Tim Bourguignon 11:48
You miss some bottle view of the summer, this first job sometimes?

Amir Saoughi 11:52
Yeah, I mean, it's like dealing with customers is is a different world. So you can iterate a lot faster without having to deal with customers. But I think the impact is so much more worth it. Because you can see, you know, based on the different industries, whether it's like finance or healthcare, manufacturing or transportation or media, you know, you're just see like, a lot more like how your software impacts the world

Tim Bourguignon 12:14
talking about Rex but I'm not familiar with the with the company itself. It's a it's a hosting company and web hosting or something like that.

Amir Saoughi 12:20
Yeah. So Rackspace was my second job. At that time, they had launched their public cloud infrastructure, using OpenStack, which was a kind of open source cloud operating system, if you will, most people these days are familiar with like Kubernetes, it was kind of an attempt at a cloud operating system prior to Kubernetes. And yeah, at that time, I worked on the networking cloud networking service. So yeah, I still at that point wasn't, you know, working directly with customers, because like compute, networking, and storage are kind of these like fundamental building blocks of cloud computing infrastructure. At that time, I still kind of abstracted away from customers. But as my journey goes, you'll see I'm getting closer and closer to customers. So they they were providing public cloud infrastructure at that time,

Tim Bourguignon 13:02
what is the deliberate choice to go into power user or developer tools? And being in the, as you said, in the, in the networking, part of that so really extracted away from the customers was it wasn't a choice, or was it an opportunity, and just to get,

Amir Saoughi 13:17
it was a choice for me to work on, like open source, everything in my first job was proprietary and closed. And so getting exposure to open source and seeing the rise of GitHub, also, at the same time I had this job, that's actually where I started taking online courses around the latest machine learning techniques, and actually led like a local study group around that. So I think open source and definitely less stressful than my first job, because I was also working remotely. So I think that kind of gave me some benefits to kind of expand my own curiosity, again, to kind of learn more on my own about machine learning.

Tim Bourguignon 13:56
So obviously, your next step will be machine learning, right?

Amir Saoughi 13:58
I mean, yeah, my first job, I was kind of getting in machine learning infrastructure in the closed world, I guess. And then second job was working on enterprise infrastructure. And then, yeah, I guess my third job, once I've moved to Amazon was doing enterprise infrastructure. But also with machine learning. I got to combine the first two again, into a new job at Amazon, I worked at AWS on sage maker on the machine learning algorithms that are built into the platform. So if you've ever used like K means or PCA are the kind of built in algorithms available on sage maker, I helped

Tim Bourguignon 14:32
build the cloud. How do we get a job at tangible us nowadays?

Amir Saoughi 14:35
Yeah, they hire lots of people. So as a as a big organization that are growing very quickly, I think they have lots of entry level positions to very senior level positions available. And when I started in New York at AWS, we just had maybe the totality was like one or two floors of the building. Now there are several several buildings across the city. So they've definitely expanded their footprint in New York City and it was great to be part of that growth.

Tim Bourguignon 15:02
Was it what you expected? When you started that you were us? Were you surprised with with the way they were the way they do things?

Amir Saoughi 15:09
Yeah, I mean, Amazon's pretty famous for having its leadership principles. Do they have 12. And they might have changed it since I've left. But while the leadership principles that kind of guides their own cultural operating system, if you will, and yeah, meetings are conducted a certain way that are different than previous organizations I worked for, and I guess the structure has been well documented in several books, it was amazing to see like how quickly they're able to being part of it, like grow, and then like, deliver on that growth, and then iterate each year. So the initial PageMaker launch was November 2017, and kept on iterating. And expanding that machine learning offering. And that was a great journey to be part of,

Tim Bourguignon 15:51
um, we're about leadership principles, but not about this meeting, both the other way running meetings, can you expand a little bit on that?

Amir Saoughi 15:57
Yeah, depending on if you're having like a team meeting, those might be different. But like, once you're having a meeting with more senior staff members, it's more document driven, the first five to 10 minutes of a meeting are spent kind of reading a document. And one of the big things there was, let's say, we're starting a new project, and we're kind of de risking and disambiguating project, there was even like feedback about your document should be structured in terms of like, you know, most risky things to like, least risky things, so that we use the appropriate amount of time on each item. So having very efficient meetings, you know, there's also the two pizza rule where you want to have relevant amount of people in the room and not more than that. And to Pizza rule also applies to like team sizes, you know, teams are six to eight people. And they've kind of expanded organizations based on that kind of building block of team size,

Tim Bourguignon 16:47
this way of working, is it something you took over into your mixer,

Amir Saoughi 16:50
I spent a lot of time writing, and I think putting your thoughts down into writing really clarifies your writing, and it makes it a lot more crisp. I think that's definitely a huge skill I took into my current role at Banco and at a startup things tend to be just more fast and loose, just because you have to adapt quickly. And obviously, if it's just me and the CEO, the engine, you know, writing a huge document doesn't make the most sense, right. So. So yeah, when I joined PyCon, it's kind of the first engineering hire. And that was back in 2019. And yeah, we've since grown to a staff of over a dozen folks and growing before

Tim Bourguignon 17:30
we go into PyCon, why did you leave AWS? You spent two years I think they don't write something like something like this?

Amir Saoughi 17:36
Yeah, less than three years. So my director ATBS Ito Liberty left Amazon to start PyCon. And because I had such a great working relationship with Ido.

Tim Bourguignon 17:49
Stay with us. We'll be right back.

Tim Bourguignon 17:51
Hello imposters, if you work in tech want to work in tech, or are tech curious in any way you'll want to listen to this. We've launched a community of professionals who come together to share information and advice about jobs, roles, careers, and the journeys we all take throughout our lives as the designers, builders, fixers investigators, explainers and protectors of the world's technology. We call it the impostor syndrome network. And all are welcome. So find the impostor syndrome network podcast, wherever you listen to find podcasts, and look for the isn community on your favorite social platform. Hashtag impostor network.

Amir Saoughi 18:33
I joined him to be the first engineering hire. At that point, I think the arch of my trajectory. I had been, you know, working in big companies for the most part. And so now is kind of looking for startup experience. And you know, eventually I would like to found my own company. And so getting experience at a startup was it was important.

Tim Bourguignon 18:52
Let's come to Blanco Why did you follow this directory? What was so attracted to you that you say, hey, yeah, I want to get out of AWS and start this experience

Amir Saoughi 19:01
with PyCon. We're building Dr. Similarity search as a service. So from working on sage maker, we had seen kind of the machine learning infrastructure needs continue to grow and grow and grow. And one of the key areas that people using machine learning in production need to help with is vector search. So vector search, basically, if you think about it is powering many different applications. So it's powering feed ranking, powering recommendation systems anomaly detection deduplication date matching has many potential use cases. So it was such a big potential market and the market continues to grow that I saw that this was a great rocketship to be a part of as we've taken off

Tim Bourguignon 19:44
you mentioned when we were talking about your second job that you went one step closer to the customers each time you took a new job are you here right with the customers now?

Amir Saoughi 19:53
Yeah, certainly I startup Yeah, wear many hats, including sales engineering, like working directly with the customer solve their problems. And having done that several times now, and I would say yeah, the spectrum at AWS, they're a bit more customer focused and customer obsession is kind of one of their key focuses there. The now Yeah, working directly with customers at startup wearing lots of hats. It's been amazing to see like, how we start the customer journey, like just meeting them for the first time. Are they then hearing about us from different outlets like this podcast or different marketing channels, and then seeing them grow with us over time as they use pine cone to power their similarity search use cases?

Tim Bourguignon 20:33
What are the kinds of users you're you're aiming for? How would you describe them?

Amir Saoughi 20:37
There's a spectrum of users. I think, right now, the most common use cases we have are people that have models, and they want to get them into production. And so they have a way to do basically vector encoding, which is, you know, you take one user and one item, and you can kind of compare them to see how similar they are. But then they want to do that at scale with, you know, millions of items, and 10s of 1000s of queries per second. And so they they need support with the heavy lifting of that vector similarity search problem. So that's where we've been the most helpful in that kind of scale, and speed and accuracy, kind of been helping them navigate those trade offs.

Tim Bourguignon 21:19
Are you producing some kind of software to install and hook up to their way of doing or is it a SAS? I sold comm to really figure out what exactly is the offering? Or is it consultancy? You know, helping them really find the right solution for them? I'm the true, I'm placing it right? In my mind. PyCon

Amir Saoughi 21:34
offers managed service. So you can you can go to our website, like bank on.io and sign up for an API key. And it's yes, solving that core vector, similar search problem. So right now, you would bring us your vectors into the pine cone similarity search service, we provide the service software as a service to do those queries as an API. Okay.

Tim Bourguignon 21:58
So as I'm bringing my data to you, and you're solving basically the problem with big air quotes, and now I'm interfacing through you to get my data via your vectors, yeah,

Amir Saoughi 22:08
you can think of it as kind of auxilary Database as a Service. So you have some core way to, let's say, you have product recommendation system, and you have millions of products in your catalog, and you want to power vector search using that. So basically, you can use the deep learning model to encode each product into a vector, and then you would insert those vectors into pine cone. And you do that for those millions of items. And then you can also do that for the millions of users. Let's say we represent users as contents of their cart, checkout, and you can encode that card also into a vector and same space. And then basically, you can query then becomes the current vector. And then the response becomes, you know, what are the top 20 items you should get as a products? So those are the results of the query?

Tim Bourguignon 22:57
Okay. It's starting to make sense. I'm not at all in this field. So I need to rebut that. I think it makes sense now. How did you roll evolve? At the very beginning, you said you were his first engineer, so So obviously, very hands on. And now you say, obviously, you're head of engineering, and he said, there's a dozen or a couple dozen engineers ready? How did your role evolve? How did your sense of of and how did your attention and focus evolve? Yeah,

Amir Saoughi 23:20
joined as the first engineer a couple of years ago, and we spent the first year kind of really defining the problem and, and building system and building that initial team. And now I guess we're at a point less than a dozen engineers, but we'd like to be a dozen engineers soon. So we're hiring. But I guess the different kinds of problems that we work on, basically three focus areas, one is kind of at the lowest level, coming back to that C++, numerical algorithms, lowest level where like the for vector engine is and then we have like a distributed data systems problem, because you can observe your vectors into pine cone in real time. And so you want to make sure we don't lose your vectors, obviously. But we also want to reflect those new vectors in your index in a very quick way. So we have Yeah, we have kind of a numerical algorithms, a set of problems, we have distributed data system problems. And then we also have packaging the product and growth of the product set of problems. So we have our team kind of focused on those three areas. And so at the beginning, I was kind of focused on the first two but then kind of over time expanding my scope to like all three and then now hiring the team to fill roles and all those three areas

Tim Bourguignon 24:35
where you already ready to work on those three or four if you can't hiring and this all management side where you already already ready for that for those tasks, or is it something you learned on the fly?

Amir Saoughi 24:48
I think there's something I learned on the fly and kind of hired out to build a team. Prior to this. I hadn't been doing any management had been like doing tech lead work, which is kind of rare. but not the same skill set, you know, I had experience with C++ and numerical algorithms and the low level stuff and distributed a systems, I would say I'm more of a distributed machine learning systems, guys. So also hiring the team to build out distributed systems. So he spent kind of building a team to kind of fill that and just managing in general, I think, yeah, where we are today, we're the way Ito would describe it as like kind of more guerrilla warfare, though, tactically, so very flat, just getting ready for that next level of growth and scaling the team and and building the building the organization. So it's, it's something that I've been learning on the job,

Tim Bourguignon 25:39
how do you approach a central problem? You say, for instance, distributed data system, not really your stuff you knew, but you were more on the on the ML side of it. And now you need to hire for this field, you're not an expert in how do you approach such a problem,

Amir Saoughi 25:52
and you're just spending time at the problem for sure gets you acquainted for like, what kind of profile you're looking for that can help you with the problem that you're solving did a lot of that made some lessons learned on building prototypes and learning from Oh, prototype would work in this setting. And very early on, like, Okay, we'll need someone to build, you know, this sub system out where we can durably store you know, the vectors. And so just Yeah, understanding the kind of the high level requirements, the use cases and the constraints that we need to fulfill. And then like looking at here are some people that work at different database companies, or have dealt with this data problems in the past and matching that kind of profile against needing to hire some basically senior engineer for the first hire for that.

Tim Bourguignon 26:38
So if I tried to rephrase that you try to find or to define a pre precise problem to tackle and then find somebody who's pretty senior who definitely had this problem already, and can solve this one, and maybe some others around it. Hopefully, some of those around it did. Did I get that? Right?

Amir Saoughi 26:54
Yeah, I think the distributed AI systems is kind of like a key part of what we're building that's a bit different than now that we have a key expertise will kind of support that person with more junior folks will say that, I mean, they could be senior, but not necessarily have to be now that we have a key folks in place for getting the system off the ground. And so building the team's productivity from there, it's just like, Okay, well, obviously, you can't just have one this year, we're a systems person, right? We will support them with more people.

Tim Bourguignon 27:23
How do you see your role evolving? If everything goes right, I suppose you're gonna grow pretty fast. So you're gonna be a company of 20? Pretty soon and then 50? And then 150? How do you see your role evolving in there? Yeah, my

Amir Saoughi 27:36
role will have to evolve over time as, as the company needs, yeah, day to day, kind of focus on things that you want to execute, and you have to ruthlessly prioritizing things. And then I guess, when you zoom out, you want to see that, you know, you know, as a startup, you kind of have to look at the metrics you want to hit and and see things grow in a certain way. And kind of working with the senior leadership team and figuring out what gaps you have and how you can address them to basically think of it as like re interviewing for your position at the next level of of growth. I mean, I started up, you know, things change rapidly. So if you're in a role today, you might, you know, move into a different role tomorrow. It's very challenging, especially when you're at length fewer than 30 people things change very quickly. Yeah,

Tim Bourguignon 28:23
absolutely. Amen. But at some point, you will face the inflection point of leaving the code behind and drifting toward pure engineering management or leaving management behind and coming back to the tech. How would you deal with such a questioning in your heart?

Amir Saoughi 28:38
I haven't solved the dilemma. Yeah, so that's I'm just being waxing extemporaneously here. But yeah, I think it's it's a hard switch. Like I was saying, like the skill set is very different. Yeah, it depends on Yeah, number of factors. That's yeah, I don't have a good answer for this question. Let's get on to something else.

Tim Bourguignon 29:00
When I look back on the story, you just tell you just hope it sounds very, very logical you really went from from one one place to the other building on top of all of the previous one. So first, the frequency trading really building the base blocks and then going more enterprise products more facing customers coming closer to customers and then even even further or always grabbing some more skills, etc. Almost. Sounds too good to be true. Did you have some some some advice during this journey, we say that that's really helped me craft this, this fairy tale where the the air quotes, again, really drive in and lead you through this journey?

Amir Saoughi 29:37
You know, we're not, you know, the first engineers and hopefully not the last engineers. So like, there's a lot of good advice out there on how to uplevel your skills. And I think something I do frequently is just like looked at LinkedIn as a very good resource. And like, I see Oh, how did this person few years ahead of me get to where they are and at Think about even like reflexively not even reaching out to them. But just like, you know, if they were going to give me advice in a few years, what would they say? And then just like reflexively giving yourself advice, I guess it's like a just to understand, like how people get to the different as, and also, obviously, this podcast is kind of reflective of that as well, most basic advice I can give is to just try out different things and follow your curiosity. That's, I mean, certainly what I did, and like, there's a bunch of different things I try on my personal life that don't pan out. And so like, I think it's good to stretch yourself. And, and then, you know, take your lessons learned and and if you can apply them to your career as well, then that works as well.

Tim Bourguignon 30:40
Awesome. Did you did you try that too, to look at someone on LinkedIn and really ask them if I want to become what you are today? What should I do?

Amir Saoughi 30:48
Yeah, I haven't like literally message them. But that's kind of something I do as like a thought exercise is also like a thought exercise about like, think of yourself at 80 years old, and write yourself a letter to your current self as your 80 year old self. And there's also like Jeff Bezos says, like the whole regret minimization framework were similar exercise like you think about yourself 80 years old. And you know, if you're already 80 years old, listening to this, if you're 100 years old, and like, minimize what you would regret at that age. So yeah, I think that that kind of guides, guys, a lot of my decision,

Tim Bourguignon 31:19
I'll have to add links to all those leadership principles, meeting policy, the regret minimization framework was all very interesting, interesting resources. I'll add that to the show notes. Were would be the best place to to reach out to you and continue the discussion with you.

Amir Saoughi 31:34
Oh, sure. Yeah, I'm available on Twitter. It's probably the easiest way for people to follow me or DM me, or what have you. Prints honest is my handle. I'm also LinkedIn. And I have a personal website. But I haven't updated that in a while. But yeah, all three work at work, if you want to reach me

Tim Bourguignon 31:53
on LinkedIn, so people can can stalk you and see what you did. And you mentioned how, what what they could ask, if they ask you, how can I become head of engineering somewhere? Do you have anything timely or no time that you want to plug in before we call it our

Amir Saoughi 32:07
hiring at PyCon? So if you're interested in the early stage startup journey, working on challenging machine learning problems or hiring in engineering, sales, marketing, yeah, so have a [email protected].

Tim Bourguignon 32:19
And we'll add all those links in the show notes. Just thank you very much. It's been a blast. Yeah, thank you. And this has been another episode of developer's journey, and with each other next week. Thanks a lot for tuning in. I hope you have enjoyed this week's episode. If you liked the show, please share rate and review. It helps more listeners discover those stories. You can find the links to all the platforms to show appears on on our website, Dev journey dot info slash subscribe. Creating the show every week takes a lot of time, energy, and of course money. Would you please help me continue bringing out those inspiring stories every week by pledging a small monthly donation, you'll find our patreon link at Deaf journey dot info slash donate. And finally, don't hesitate to reach out and tell me how this week story is shaping your future. You can find me on Twitter at @timothep ti m o t h e p or per email info at Dev journey dot info. Talk to you soon.